我有一個這樣的多索引數據集： mean std Happiness Score Happiness ScoreRegion Australia and New Zealand 7.302500 0.020936Central and Eastern Europe 5.371184 0.578274Eastern Asia 5.632333 0.502100Latin America and Caribbean 6.069074 0.728157Middle East and Northern Africa 5.387879 1.031656North America 7.227167 0.179331Southeastern Asia 5.364077 0.882637Southern Asia 4.590857 0.535978Sub-Saharan Africa 4.150957 0.584945Western Europe 6.693000 0.777886我想按標準偏差對其進行排序。我的嘗試：import numpy as npimport pandas as pddf1.sort_values(by=('Region','std'))如何解決問題？
3 回答
紫衣仙女
TA貢獻1839條經驗 獲得超15個贊
設置
np.random.seed(0)
df = pd.DataFrame(np.random.choice(10, (5, 2)))
df.columns = pd.MultiIndex.from_arrays([['mean', 'std'], ['Happiness Score'] * 2])
df
mean std
Happiness Score Happiness Score
0 5 0
1 3 3
2 7 9
3 3 5
4 2 4
您可以使用argsort和重新索引df：
df.loc[:, ('std', 'Happiness Score')].argsort().values
# array([0, 1, 4, 3, 2])
df.iloc[df.loc[:, ('std', 'Happiness Score')].argsort().values]
# df.iloc[np.argsort(df.loc[:, ('std', 'Happiness Score')])]
mean std
Happiness Score Happiness Score
0 5 0
1 3 3
4 2 4
3 3 5
2 7 9
另一個解決方案是sort_values，傳遞一個元組：
df.sort_values(by=('std', 'Happiness Score'), axis=0)
mean std
Happiness Score Happiness Score
0 5 0
1 3 3
4 2 4
3 3 5
2 7 9
我認為您的想法是正確的，但是元組的順序不正確。
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